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Real-time portrait animation is essential for interactive applications such as virtual assistants and live avatars, requiring high visual fidelity, temporal coherence, ultra-low latency, and responsive control from dynamic inputs like…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Steven Xiao , Xindi Zhang , Dechao Meng , Qi Wang , Peng Zhang , Bang Zhang

We present a novel approach for generating 360-degree high-quality, spatio-temporally coherent human videos from a single image. Our framework combines the strengths of diffusion transformers for capturing global correlations across…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Ruizhi Shao , Youxin Pang , Zerong Zheng , Jingxiang Sun , Yebin Liu

In this work, we propose a new diffusion-based method for video frame interpolation (VFI), in the context of traditional hand-made animation. We introduce three main contributions: The first is that we explicitly handle the interpolation…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Victor Fonte Chavez , Claudia Esteves , Jean-Bernard Hayet

Existing mobile devices are constrained by compact optical designs, such as small apertures, which make it difficult to produce natural, optically realistic bokeh effects. Although recent learning-based methods have shown promising results,…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Linxiao Shi , Siming Zheng , Zerong Wang , Hao Zhang , Jinwei Chen , Bo Li , Shifeng Chen , Peng-Tao Jiang

Hand-drawn character animation is a vibrant field in computer graphics, presenting challenges in achieving geometric consistency while conveying expressive motion. Traditional skeletal animation methods maintain geometric consistency but…

Graphics · Computer Science 2025-09-09 Jie Zhou , Linzi Qu , Miu-Ling Lam , Hongbo Fu

We have recently seen tremendous progress in diffusion advances for generating realistic human motions. Yet, they largely disregard the multi-human interactions. In this paper, we present InterGen, an effective diffusion-based approach that…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Han Liang , Wenqian Zhang , Wenxuan Li , Jingyi Yu , Lan Xu

Image fusion seeks to seamlessly integrate foreground objects with background scenes, producing realistic and harmonious fused images. Unlike existing methods that directly insert objects into the background, adaptive and interactive fusion…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Junjia Huang , Pengxiang Yan , Jiyang Liu , Jie Wu , Zhao Wang , Yitong Wang , Liang Lin , Guanbin Li

The video generation field has witnessed rapid improvements with the introduction of recent diffusion models. While these models have successfully enhanced appearance quality, they still face challenges in generating coherent and natural…

Computer Vision and Pattern Recognition · Computer Science 2025-04-21 Yaosi Hu , Zhenzhong Chen , Chong Luo

Text-to-video (T2V) diffusion models have shown promising capabilities in synthesizing realistic videos from input text prompts. However, the input text description alone provides limited control over the precise objects movements and…

Computer Vision and Pattern Recognition · Computer Science 2025-02-20 Yen-Siang Wu , Chi-Pin Huang , Fu-En Yang , Yu-Chiang Frank Wang

Video virtual try-on aims to transfer a clothing item onto the video of a target person. Directly applying the technique of image-based try-on to the video domain in a frame-wise manner will cause temporal-inconsistent outcomes while…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Zixun Fang , Wei Zhai , Aimin Su , Hongliang Song , Kai Zhu , Mao Wang , Yu Chen , Zhiheng Liu , Yang Cao , Zheng-Jun Zha

Despite recent progress in video generation, producing videos that adhere to physical laws remains a significant challenge. Traditional diffusion-based methods struggle to extrapolate to unseen physical conditions (eg, velocity) due to…

Computer Vision and Pattern Recognition · Computer Science 2025-04-23 Wang Lin , Liyu Jia , Wentao Hu , Kaihang Pan , Zhongqi Yue , Wei Zhao , Jingyuan Chen , Fei Wu , Hanwang Zhang

Diffusion-based video generation can create realistic videos, yet existing image- and text-based conditioning fails to offer precise motion control. Prior methods for motion-conditioned synthesis typically require model-specific…

Computer Vision and Pattern Recognition · Computer Science 2025-11-13 Assaf Singer , Noam Rotstein , Amir Mann , Ron Kimmel , Or Litany

Text-guided video-to-video stylization transforms the visual appearance of a source video to a different appearance guided on textual prompts. Existing text-guided image diffusion models can be extended for stylized video synthesis.…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Minshan Xie , Hanyuan Liu , Chengze Li , Tien-Tsin Wong

Recent advances in text-to-video diffusion models have enabled high-quality video synthesis, but controllable generation remains challenging, particularly under limited data and compute. Existing fine-tuning methods for conditional…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Kinam Kim , Junha Hyung , Jaegul Choo

Generating realistic time series data is critical for applications in healthcare, finance, and science. However, irregular sampling and missing values present significant challenges. While prior methods address these irregularities, they…

Machine Learning · Computer Science 2025-10-09 Gal Fadlon , Idan Arbiv , Nimrod Berman , Omri Azencot

Event-based video reconstruction has garnered increasing attention due to its advantages, such as high dynamic range and rapid motion capture capabilities. However, current methods often prioritize the extraction of temporal information…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Lin Zhu , Yunlong Zheng , Yijun Zhang , Xiao Wang , Lizhi Wang , Hua Huang

We present a method for generating video sequences with coherent motion between a pair of input key frames. We adapt a pretrained large-scale image-to-video diffusion model (originally trained to generate videos moving forward in time from…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Xiaojuan Wang , Boyang Zhou , Brian Curless , Ira Kemelmacher-Shlizerman , Aleksander Holynski , Steven M. Seitz

Recent advancements in human video synthesis have enabled the generation of high-quality videos through the application of stable diffusion models. However, existing methods predominantly concentrate on animating solely the human element…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Jinlin Liu , Kai Yu , Mengyang Feng , Xiefan Guo , Miaomiao Cui

While diffusion models have shown impressive performance in 2D image/video generation, diffusion-based Text-to-Multi-view-Video (T2MVid) generation remains underexplored. The new challenges posed by T2MVid generation lie in the lack of…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Bing Li , Cheng Zheng , Wenxuan Zhu , Jinjie Mai , Biao Zhang , Peter Wonka , Bernard Ghanem

Long video generation remains a challenging and compelling topic in computer vision. Diffusion based models, among the various approaches to video generation, have achieved state of the art quality with their iterative denoising procedures.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Siyang Zhang , Harry Yang , Ser-Nam Lim